Wireless communication networks, such as cellular networks, operate by sharing resources among the mobile terminals operating in the communication network. As part of the sharing process, resources relating to assigned channels, codes, etc. are allocated by one or more controlling devices within the system. Certain types of wireless communication networks, e.g., orthogonal frequency division multiplexed (“OFDM”) networks, are used to support cell-based high speed services such as those under certain standards such as the 3rd Generation Partnership Project (“3GPP”) and 3GPP2 evolutions, e.g., Long Term Evolution (“LTE”), the Ultra-Mobile Broadband (“UMB”) broadband wireless standard and the IEEE 802.16 standards. The IEEE 802.16 standards are often referred to as WiMAX or less commonly as WirelessMAN or the Air Interface Standard.
OFDM technology uses a channelized approach and divides a wireless communication channel into many sub-channels which can be used by multiple mobile terminals at the same time. These sub-channels and hence the mobile terminals can be subject to interference from adjacent cells and other mobile terminals because neighboring base stations and mobile terminals can use the same frequency blocks. The result is that spectral efficiency is reduced, thereby reducing both communication throughput as well as the quantity of mobile terminals that can be supported in the network.
This problem is further exacerbated in multiple input, multiple output (“MIMO”) environments. Multiple Input, Multiple Output Orthogonal Frequency Division Multiplexing (“MIMO-OFDM”) is an OFDM technology that uses multiple antennas to transmit and receive radio signals. MIMO-OFDM allows service providers to deploy wireless broadband systems that take advantage of the multi-path properties of environments using base station antennas that do not necessarily have line of sight communications with the mobile terminal.
MIMO systems use multiple antennas to simultaneously transmit data, in small pieces to the receiver, which processes the separate data transmissions and puts them back together. This process, called spatial multiplexing, can be used to proportionally boost the data-transmission speed by a factor equal to the number of transmitting antennas. In addition, since all data is transmitted both in the same frequency band and with separate spatial signatures, this technique utilizes spectrum very efficiently.
MIMO operation implements a channel matrix (N×M) where N is the number of transmit antennas and M is the number of receive antennas to define the coding and modulation matrix for the wireless communication channel as a whole. The less correlated each column in the matrix is, the less interference experienced in each channel (as a result of the multiple antennas). In the case where there is a totally uncorrelated arrangement, i.e., the dot product between columns is zero, the channels are considered orthogonal to one another. Orthogonality provides the least antenna-to-antenna interference, thereby maximizing channel capacity, and data rate due to the higher post-processing signal to interference and noise ratio (“PP-SINR”). PP-SINR is the SINR after the MIMO decoding stage.
Virtual MIMO (“V-MIMO”) implements the MIMO technique described above by using multiple simultaneously transmitting mobile terminals each having one or more antennas. The serving base station includes multiple antennas. Although the base station can treat virtual MIMO operation as traditional MIMO in which a single mobile terminal has multiple antennas and can separate and decode the transmissions from the multiple simultaneously transmitting mobile terminals, channel correlation among mobile terminals as discussed above results in channel capacity loss due to inter-mobile terminal interference. Scheduling the transmissions from the multiple mobile terminals to share channel resources can provide system capacity gain (also referred to as “scheduling gain”). It is therefore desirable to have a virtual MIMO arrangement that maximizes system capacity through the use of scheduling gain.
It is known that orthogonality-based scheduling can reduce inter-mobile terminal interference. However, this arrangement only works well in narrow-band implementations because the channel characteristics, e.g., attenuation, phase, etc., do not significantly change because the channel is almost constant in the frequency band. In other words, the channel matrix that defines the channel also does not significantly change. In contrast, wideband diversity channel implementations, such as OFDM, can result in different channel characteristics across the frequency band. The result is that a wideband diversity channel that is orthogonal at one point does not mean that the channel is orthogonal at a different spot within the channel. Hence, orthogonality based scheduling is likely ineffective in wideband implementations.
Arrangements for MIMO wideband transmission scheduling are known. For example, it is known to schedule MIMO transmission by matching the modulation coding set (“MCS”) of each layer, where a layer is an independent parallel transmitted data stream, i.e., data streams from multiple mobile terminals in a virtual MIMO environment, to the channel quality indicator (“CQI”) of that layer. However, using these known techniques, the CQI of each layer is computed according to the post-processing effective SINR, i.e., after spacial processing by the base station. The undesirable result is that this arrangement is processing intensive and does not adequately exploit the channel capacity. It is therefore further desirable to have a scheduling arrangement that can be implemented in OFDM virtual MIMO environments to support, for example, WiMAX communications such that channel capacity is used in as efficient a manner as possible.